Description

Blackwell Publishing is delighted to announce that this book has been Highly Commended in the 2004 BMA Medical Book Competition. Here is the judges' summary of this book:

"This is a technical book on a technical subject but presented in a delightful way. There are many books on statistics for doctors but there are few that are excellent and this is certainly one of them. Statistics is not an easy subject to teach or write about. The authors have succeeded in producing a book that is as good as it can get. For the keen student who does not want a book for mathematicians, this is an excellent first book on medical statistics."

Essential Medical Statistics is a classic amongst medical statisticians. An introductory textbook, it presents statistics with a clarity and logic that demystifies the subject, while providing a comprehensive coverage of advanced as well as basic methods.

The second edition of Essential Medical Statistics has been comprehensively revised and updated to include modern statistical methods and modern approaches to statistical analysis, while retaining the approachable and non-mathematical style of the first edition. The book now includes full coverage of the most commonly used regression models, multiple linear regression, logistic regression, Poisson regression and Cox regression, as well as a chapter on general issues in regression modelling. In addition, new chapters introduce more advanced topics such as meta-analysis, likelihood, bootstrapping and robust standard errors, and analysis of clustered data.

Aimed at students of medical statistics, medical researchers, public health practitioners and practising clinicians using statistics in their daily work, the book is designed as both a teaching and a reference text. The format of the book is clear with highlighted formulae and worked examples, so that all concepts are presented in a simple, practical and easy-to-understand way. The second edition enhances the emphasis on choice of appropriate methods with new chapters on strategies for analysis and measures of association and impact.

Essential Medical Statistics is supported by a web site at www.blackwellpublishing.com/essentialmedstats. This useful online resource provides statistical datasets to download, as well as sample chapters and future updates.

8. Using P-values and confidence intervals to interpret the results of statistical analyses.

9. Comparison of means from several groups: analysis of variance.

10. Linear Regression and Correlation.

11. Multiple Regression.

12. Goodness of fit and regression diagnostics.

13. Transformations.

Part C. Analysis of binary outcomes.

14. Probability, risks and odds (of disease).

15. Proportions and the binomial distribution.

16. Comparing two proportions.

17. Chi-squared tests for 2 × 2 and larger contingency tables.

18. Controlling for confounding: stratification.

19. Logistic regression: comparing two or more exposure groups.

20. Logisitic regression: controlling for confounding and other extensions.

21. Matched studies.

Part D. Longitudinal studies: Analysis of rates and survival times.

22. Longitudinal studies, rates and the Poisson distribution.

23. Comparing rates.

24. Poisson regression.

25. Standardisation.

26. Survival analysis: displaying and comparing survival patterns.

27. Regression analysis of survival data.

Part E. Statistical modelling.

28. Likelihood.

29. Regression modelling.

30. Relaxing model assumptions.

31. Analysis of clustered data.

32. Systematic reviews and meta-analysis.

33. Bayesian statistics.

Part F. Study design, analysis and interpretation.

34. Linking analysis to study design: summary of methods.

35. Calculation of Required Sample Size.

36. Measurement error: assessment and implications.

37. Measures of association and impact.

38. Strategies for analysis.

APPENDIX: Statistical Tables.

Bibliography

"This book is the statistics book of choice for anyone wanting a proper appreciation of the use and application of statistics in health care. I highly recommend this book." (Journal of Renal Nursing, 6 November 2011)

the breadth of coverage of the book is excellent ... a rather different approach to teaching medical statistics." Statistics in Medicine

"The most readable book that I have yet discovered in the topic" Community Health Studies

"This book is statistically correct. That is enough to distinguish it from most of its competitors." British Medical Journal

Published Reviews of the 2th Edition

"One word which definitely describes this book is "comprehensive". Anything you ever wanted to know about medical statistics is covered in immense detail."

"This is a comprehensive book that includes an impressive range of topics often omitted from books aimed at non-statisticians.

...a resource that makes it easy for a beginner to comprehend a wide range of statistical concepts and tools. Essential Medical Statistics fills an important niche by providing practical information on a comprehensive scope of modern statistical methods and, at the same time, communicating on the same wavelengths as physicians and other nonstatisticians."

Teaching of Statistics in the Health Sciences, Section of the American Statistical Association, Spring 2004

"The book is laid out in a logical fashion and includes all of the tables you need to find p-values once you have performed a test. It covers simple statistical methods, such as how to calculate the mean and standard deviation, progressing to linear and multiple regression, Poisson regression and measures of impact and association.

...I would recommend using it to anyone who is still struggling with statistics."

North Wing, Sheffield Medics Magazine, Winter 2004

"The book is generally well laid out, the indexing is well structured and a comprehensive bibliography is provided. The topics are easy to locate and include practical examples. These attributes make it a useful text for both consulting and teaching purposes."Statistics in Medicine, Vol 24, Number 5, March 2005

This book is a classic amongst medical statisticians

Throughout, methods are illustrated with worked examples

Starts with the basic concepts in data analysis and statistical inference

Full coverage of multiple linear regression, logistic regression, Poisson regression and Cox regression, as well as general issues in regression modelling

More advanced topics include meta-analysis, likelihood, bootstrapping and robust standard errors, and analysis of clustered data

Accompanying web site with sample chapters, datasets to download, and updates, at www.blackwellpublishing.com/essentialmedstats